Initial commit: OmniAI Web Frontend

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

src/api/scriptEvalClient.ts

@@ -0,0 +1,108 @@
+import { buildApiUrl, buildAuthHeaders } from "./serverConnection";
+
+export interface ScriptEvalResult {
+  totalScore: number;
+  grade: string;
+  dimensionScores: Record<string, number>;
+  summary: string;
+  issues: string[];
+  highlights: string[];
+  suggestions: string[];
+}
+
+const EVAL_SYSTEM_PROMPT = `你是一位专业的剧本评测专家。请对用户提供的剧本进行六维评分分析，并以严格的 JSON 格式返回结果。
+
+六个评分维度：
+1. hook（钩子设计，满分20）：开篇吸引力、悬念设置、黄金三秒法则
+2. character（角色塑造，满分15）：人物立体度、动机合理性、弧光设计
+3. plot（剧情结构，满分20）：起承转合、节奏把控、冲突设计
+4. dialogue（台词对白，满分15）：语言质感、角色差异化、潜台词
+5. visual（画面表现，满分15）：镜头感、空间层次、视觉冲击力
+6. content（内容深度，满分15）：主题表达、情感共鸣、思想内核
+
+请严格按以下 JSON 格式返回（不要包含任何其他文字）：
+{
+  "dimensionScores": { "hook": 数字, "character": 数字, "plot": 数字, "dialogue": 数字, "visual": 数字, "content": 数字 },
+  "summary": "一句话总结评价",
+  "issues": ["问题1", "问题2", ...],
+  "highlights": ["亮点1", "亮点2", ...],
+  "suggestions": ["建议1", "建议2", ...]
+}`;
+
+const DIMENSION_WEIGHTS: Record<string, { maxScore: number; weight: number }> = {
+  hook: { maxScore: 20, weight: 0.2 },
+  character: { maxScore: 15, weight: 0.15 },
+  plot: { maxScore: 20, weight: 0.2 },
+  dialogue: { maxScore: 15, weight: 0.15 },
+  visual: { maxScore: 15, weight: 0.15 },
+  content: { maxScore: 15, weight: 0.15 },
+};
+
+function computeTotalAndGrade(scores: Record<string, number>): { totalScore: number; grade: string } {
+  const totalScore = Math.round(
+    Object.entries(DIMENSION_WEIGHTS).reduce((sum, [key, dim]) => {
+      const score = Math.max(0, Math.min(dim.maxScore, scores[key] ?? 0));
+      return sum + (score / dim.maxScore) * 100 * dim.weight;
+    }, 0),
+  );
+  const grade = totalScore >= 90 ? "S" : totalScore >= 80 ? "A" : totalScore >= 70 ? "B" : totalScore >= 60 ? "C" : "D";
+  return { totalScore, grade };
+}
+
+function extractJson(text: string): unknown {
+  const fenced = text.match(/```(?:json)?\s*([\s\S]*?)```/);
+  const raw = fenced ? fenced[1].trim() : text.trim();
+  return JSON.parse(raw);
+}
+
+export async function evaluateScript(script: string, signal?: AbortSignal): Promise<ScriptEvalResult> {
+  const res = await fetch(buildApiUrl("ai/chat"), {
+    method: "POST",
+    headers: buildAuthHeaders(),
+    body: JSON.stringify({
+      model: "qwen3.7-max",
+      messages: [
+        { role: "system", content: EVAL_SYSTEM_PROMPT },
+        { role: "user", content: `请评测以下剧本：\n\n${script.slice(0, 8000)}` },
+      ],
+      stream: false,
+      temperature: 0.3,
+    }),
+    signal,
+  });
+
+  if (!res.ok) {
+    throw new Error(`评测请求失败 (${res.status})`);
+  }
+
+  const payload = await res.json();
+  const content: string = payload?.choices?.[0]?.message?.content
+    ?? payload?.result?.content
+    ?? payload?.content
+    ?? payload?.text
+    ?? (typeof payload === "string" ? payload : "");
+
+  if (!content) throw new Error("模型未返回有效内容");
+
+  const parsed = extractJson(content) as Record<string, unknown>;
+  const dimensionScores: Record<string, number> = {};
+  const rawScores = parsed.dimensionScores as Record<string, number> | undefined;
+  if (!rawScores || typeof rawScores !== "object") throw new Error("评分格式异常");
+
+  for (const key of Object.keys(DIMENSION_WEIGHTS)) {
+    const val = Number(rawScores[key] ?? 0);
+    dimensionScores[key] = Math.max(0, Math.min(DIMENSION_WEIGHTS[key].maxScore, val));
+  }
+
+  const { totalScore, grade } = computeTotalAndGrade(dimensionScores);
+
+  return {
+    totalScore,
+    grade,
+    dimensionScores,
+    summary: String(parsed.summary || ""),
+    issues: Array.isArray(parsed.issues) ? parsed.issues.map(String) : [],
+    highlights: Array.isArray(parsed.highlights) ? parsed.highlights.map(String) : [],
+    suggestions: Array.isArray(parsed.suggestions) ? parsed.suggestions.map(String) : [],
+  };
+}